Delineating buildings by grouping lines with MRFs

被引:62
作者
Krishnamachari, S
Chellappa, R
机构
[1] UNIV MARYLAND, INST ADV COMP STUDIES, COLLEGE PK, MD 20742 USA
[2] COMSAT LABS, CLARKSBURG, MD 20871 USA
基金
美国国家科学基金会;
关键词
D O I
10.1109/83.481683
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Traditionally, Markov random field (MRF) models have been used in low-level image analysis. This correspondence presents an MRF-based scheme to perform object delineation. The proposed edge-based approach involves extracting straight lines from the edge map of an image. Then, an MRF model is used to group these lines to delineate buildings in aerial images.
引用
收藏
页码:164 / 168
页数:5
相关论文
共 12 条
[1]  
BESAG J, 1974, J ROY STAT SOC B MET, V36, P192
[2]  
COOPER PR, 1989, 301 U ROCH DEP COMP
[3]   STOCHASTIC RELAXATION, GIBBS DISTRIBUTIONS, AND THE BAYESIAN RESTORATION OF IMAGES [J].
GEMAN, S ;
GEMAN, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (06) :721-741
[4]   INCREMENTAL RECONSTRUCTION OF 3D SCENES FROM MULTIPLE, COMPLEX IMAGES [J].
HERMAN, M ;
KANADE, T .
ARTIFICIAL INTELLIGENCE, 1986, 30 (03) :289-341
[5]   DETECTING BUILDINGS IN AERIAL IMAGES [J].
HUERTAS, A ;
NEVATIA, R .
COMPUTER VISION GRAPHICS AND IMAGE PROCESSING, 1988, 41 (02) :131-152
[6]  
IRVIN RB, 1989, IEEE T SYST MAN CYB, V19, P1564, DOI 10.1117/12.952691
[7]   SNAKES - ACTIVE CONTOUR MODELS [J].
KASS, M ;
WITKIN, A ;
TERZOPOULOS, D .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1987, 1 (04) :321-331
[8]  
KRISHNAMACHARI S, 1993, CARTR682 U MAR TECH
[9]  
Matsuyama T., 1990, SIGMA KNOWLEDGE BASE
[10]   A MARKOV RANDOM FIELD MODEL-BASED APPROACH TO IMAGE INTERPRETATION [J].
MODESTINO, JW ;
ZHANG, J .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1992, 14 (06) :606-615